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What is the small-file problem in Spark, and how do you solve it?

Spark/Big Datahard0.7 min readPremium
Frequency
Low
Asked at 2 companies
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Daniel WellingtonIncedo
Key Concepts Tested
partitionsparkwindow
Expert AnswerPremium
131 wordsInterview-ready
Small-file problem: Too many tiny files (KB–MB) cause metadata explosion (S3/HDFS list operations), slow scans, and many small tasks. **Root causes**: High parallelism (many partitions), over-partitioning by high-cardinality key, streaming append with small batches. **Why it hurts**: S3 list costs $0.005/1000 requests; 1M files = $5 just for listing. Query engines (Athena, Presto) open each file; latency grows with file count....
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